Recognizing AI’s potential to transform economies and the need for India to strategize its approach, Hon’ble Finance Minister, in his budget speech for 2018 – 2019, mandated NITI Aayog to establish the National Program on AI, with a view to guiding the research and development in new and emerging technologies. The paper was released on 4th June, 2018.
NITI Aayog has adopted a three-pronged approach – undertaking exploratory proof-of-concept AI projects in various areas, crafting a national strategy for building a vibrant AI ecosystem in India and collaborating with various experts and stakeholders.
This paper focuses on how India can leverage the transformative technologies to ensure social and inclusive growth in line with the development philosophy of the government and lay the ground work for evolving the National Strategy for Artificial Intelligence.
The AI ecosystem is essentially based on 5 pillars: policy makers, large companies, startups, universities and multi-stakeholder partnerships.
India’s approach to AI:
The strategy should strive to leverage AI for economic growth, social development and inclusive growth, and finally as a “Garage” for emerging and developing economies. NITI Aayog has decided to focus on five sectors that are envisioned to benefit the most from AI in solving societal needs:
- Healthcare: increased access and affordability of quality healthcare,
- Agriculture: enhanced farmers’ income, increased farm productivity and reduction of wastage,
- Education: improved access and quality of education,
- Smart Cities and Infrastructure: efficient and connectivity for the burgeoning urban population,and
- Smart Mobility and Transportation: smarter and safer modes of transportation and better traffic and congestion problems.
The report identifies the following barriers that are posed before India which need to be addressed in order to achieve the goals of #AIforAll:
- Lack of broad based expertise in research and application of AI,
- Absence of enabling data ecosystems – access to intelligent data,
- High resource cost and low awareness for adoption of AI,
- Privacy and security, including a lack of formal regulations around anonymisation of data, and
- Absence of collaborative approach to adoption and application of AI.
The paper proposes a two-tiered structure to address India’s AI research aspirations:
Further, data is one of the primary drivers of AI solutions, and thus appropriate handling of data, ensuring privacy and security is of prime importance. Challenges include data usage without consent, risk of identification of individuals through data, data selection bias and the resulting discrimination of AI models, and asymmetry in data aggregation. The paper suggests establishing data protection frameworks and sectorial regulatory frameworks, and promotion of adoption of international standards. In order for India to ride the AI innovation wave, a robust intellectual property framework is required.
Synergy of IP laws and AI:
Despite a number of government initiatives in strengthening the IP regime, challenges remain, especially in respect of applying stringent and narrowly focused patent laws to AI applications – given the unique nature of AI solution development. To tackle these issues, establishment of IP facilitation centers to help bridge the gap between practitioners and AI developers, and adequate training of IP granting authorities, judiciary and tribunals has been suggested.
AI and the world:
There has been tremendous activity concerning AI policy in different countries over the past couple of years. Governments in USA, UK, France, Japan and China have released their policy and strategy papers relating to AI. AI has the potential to provide large incremental value to a wide range of sectors globally, and is expected to be the key source of competitive advantage for firms.
Paradigm of AI:
An unrelated but interesting paradigm for AI application is the “AI + X” approach. Deployment can be viewed through the paradigm of “take an existing process, and add AI” or “AI + X”; where “X” can range from tasks such as driving a car, where AI can provide incremental value through improved routing and energy management, to act of sowing seeds, where AI can help inform decision making and improve productivity.
Key Challenges: Sector Wise
The preceding analysis of focus sectors – Healthcare, Agriculture, Education, Smart Cities and Infrastructure, and Smart Mobility and Transport, highlight the potential of AI tools and technologies in transforming the sectors and state of Indian economy as a whole.
However, analyzing across the focus sectors, the challenges are concentrated across the following common themes:
- Lack of enabling data ecosystems
- Low intensity of AI research
- Core research in fundamental technologies
- Transforming core research into market applications
- Inadequate availability of AI expertise, manpower and skilling opportunities
- High resource cost and low awareness for adopting AI in business processes
- Unclear privacy, security and ethical regulations
- Unattractive Intellectual Property regime to incentivize research and adoption of AI
- Turbocharging both core and applied research. In addition, two frameworks for solving some of AI’s biggest research challenges through collaborative, market oriented approach have been proposed.
- Reskilling of existing workforce and preparing students for developing applied set of skills for the changing world of technology.
- In order to address these challenges one may focus on developing large foundational annotated data sets to democratize data and multi-stakeholder marketplaces across the AI value chain (data, annotated data and AI models).
- Lay down the challenges and suggestion for addressing some of these not so straightforward implementational challenges of AI.
- Re-skiiling of the current workforce; Recognition and standardisation of informal training institutions; Creation of open platforms for learning; Creating financial incentives for reskilling of employees;
- Indian education is in urgent need of transition particularly in subjects relevant to STEM, or computer based education and hence the implementation of AI.
- The major market segments for the increased AI adoption are:
(a) Private enterprises: mostly driven by market and enterprise considerations,
(b) Public Sector Undertakings: imperative to drive up the operational efficiency of PSUs, and
(c) Government: improve process efficiency, reduce human discretion, eliminate middlemen, advance prediction, pro-active and predictive service delivery to citizens.
Initiatives on promoting and adoption of AI in India:
- Creating a multi-stakeholder Marketplace
- Facilitating creation of large foundational annotated data sets
- Partnerships and collaboration
- Spreading awareness on the advantages AI offers
- Supporting startups
Ethics and AI:
One of the most tricky situation in implementing AI would revolved around privacy, ethics, fairness and tackling the biases in AI which would also include issues of transparency and opening the “Black Box”.